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Signs and Pedestrian Safety in Automated Transportation Systems

Received: 18 April 2019     Published: 15 June 2019
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Abstract

Motor-vehicle accidents have caused many safety concerns ever since cars have been on the road. With the implementation of cooperative and automated vehicles (CAVs) merging into the current crosswalks, signals, and concrete rules, the vehicle-pedestrian interactions create noteworthy safety issues. Through observational findings, intersections with higher signage and pedestrian signals had less likely of a chance for pedestrians to run into an altercation when compared to intersections with just crosswalks and no pedestrian signals. This research presents an optimization framework and an analytical solution with field observations to study whether the implementation of more pedestrian signals could have a great effect on vehicle/pedestrian incidents. The research implements the integrated methods of case studies, modeling and simulation using mathematical and statistical software on correlations and probabilities. This study adds minimal interference to the observations as they naturally occur. The study setting is non-contrived and maintained as natural environment. The collected data is continuous time series and measured using Chi-Square for analysis. After the identification of possible interactions between CAVs and pedestrians based on the data surveyed around the Illinois State University (ISU), this study finds that the safety of pedestrian relies on the intersection design of signs and signals more than the intelligence of CAVs (significance level = 95%). This paper also discusses law enforcement and autonomous driving as a means of lowering pedestrian incidents at intersections. The developed mathematical analysis model and simulations help to verify the influences of transportation signs and intersection designs. The investigation innovatively demonstrates the feasibilities of different methods to protect the pedestrian safety while they enter intersections. The findings from this research can provide decision support for future transportation design and implementation rules of CAVs.

Published in Automation, Control and Intelligent Systems (Volume 7, Issue 1)
DOI 10.11648/j.acis.20190701.16
Page(s) 46-53
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Cooperative and Automated Vehicles (CAVs), Pedestrian, Safety, Signal Design, Crosswalk Analysis

References
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[4] Jome, E. (2018, September 5). Freshman and graduate student numbers up at Illinois State. Retrieved from Illinois State University news: https://news.illinoisstate.edu/2018/09/freshman-and-graduate-student-numbers-up-at-illinois-state/
[5] Monsere, C. M., Kothuri, S., Rampa, A., & Figliozzi, M. A. (2018). An Analysis of the Safety Effectiveness of pedestrian Crossing Enhancements in Oregon. Transportation Board 97th Anual Meeting, 17. Retrieved from https://trid.trb.org/view/1494553.
[6] Kwigizile, V., Oh, J.-S., Van Houten, R., Prieto, D., Boateng, R., Rodriguez, L., Andridge, P. (2015). Evaluation of Michigan's Engineering Improvement for Older Drivers. Western Michigan University, Kalamazoo; Michigan Department of Transportation, 148. Retrieved from https://trid.trb.org/view/1371139.
[7] Hu, W. (2017, November 24). Giving Pedestrians a Head Start Crossing Streets. Retrieved from New York Times: https://www.nytimes.com/2017/11/24/nyregion/pedestrians-new-york-walk-signals.html.
[8] Retting, R. A., Ferguson, S. A., & McCartt, A. T. (2003). A Review of Evidence-Based Traffic Engineering Measures Designed to Reduce Pedestrian–Motor Vehicle Crashes. American Journal of Public Health, 1456-1463. Retrieved from https://ajph.aphapublications.org/doi/pdf/10.2105/AJPH.93.9.1456.
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[16] Pollack, K. M., Gielen, A. C., Mohad Ismail, M. N., Mitzner, M., Wu, M., & Links, J. M. (2014). Investigating and improving pedestrian safety in an urban environment. Injury Epidemiology, 1-9. Retrieved from https://www.ncbi.nlm.nih. gov/pmc/articles/PMC5005641/.
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Cite This Article
  • APA Style

    Haiyan Xie, Luke Verplaetse. (2019). Signs and Pedestrian Safety in Automated Transportation Systems. Automation, Control and Intelligent Systems, 7(1), 46-53. https://doi.org/10.11648/j.acis.20190701.16

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    ACS Style

    Haiyan Xie; Luke Verplaetse. Signs and Pedestrian Safety in Automated Transportation Systems. Autom. Control Intell. Syst. 2019, 7(1), 46-53. doi: 10.11648/j.acis.20190701.16

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    AMA Style

    Haiyan Xie, Luke Verplaetse. Signs and Pedestrian Safety in Automated Transportation Systems. Autom Control Intell Syst. 2019;7(1):46-53. doi: 10.11648/j.acis.20190701.16

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  • @article{10.11648/j.acis.20190701.16,
      author = {Haiyan Xie and Luke Verplaetse},
      title = {Signs and Pedestrian Safety in Automated Transportation Systems},
      journal = {Automation, Control and Intelligent Systems},
      volume = {7},
      number = {1},
      pages = {46-53},
      doi = {10.11648/j.acis.20190701.16},
      url = {https://doi.org/10.11648/j.acis.20190701.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20190701.16},
      abstract = {Motor-vehicle accidents have caused many safety concerns ever since cars have been on the road. With the implementation of cooperative and automated vehicles (CAVs) merging into the current crosswalks, signals, and concrete rules, the vehicle-pedestrian interactions create noteworthy safety issues. Through observational findings, intersections with higher signage and pedestrian signals had less likely of a chance for pedestrians to run into an altercation when compared to intersections with just crosswalks and no pedestrian signals. This research presents an optimization framework and an analytical solution with field observations to study whether the implementation of more pedestrian signals could have a great effect on vehicle/pedestrian incidents. The research implements the integrated methods of case studies, modeling and simulation using mathematical and statistical software on correlations and probabilities. This study adds minimal interference to the observations as they naturally occur. The study setting is non-contrived and maintained as natural environment. The collected data is continuous time series and measured using Chi-Square for analysis. After the identification of possible interactions between CAVs and pedestrians based on the data surveyed around the Illinois State University (ISU), this study finds that the safety of pedestrian relies on the intersection design of signs and signals more than the intelligence of CAVs (significance level = 95%). This paper also discusses law enforcement and autonomous driving as a means of lowering pedestrian incidents at intersections. The developed mathematical analysis model and simulations help to verify the influences of transportation signs and intersection designs. The investigation innovatively demonstrates the feasibilities of different methods to protect the pedestrian safety while they enter intersections. The findings from this research can provide decision support for future transportation design and implementation rules of CAVs.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Signs and Pedestrian Safety in Automated Transportation Systems
    AU  - Haiyan Xie
    AU  - Luke Verplaetse
    Y1  - 2019/06/15
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    N1  - https://doi.org/10.11648/j.acis.20190701.16
    DO  - 10.11648/j.acis.20190701.16
    T2  - Automation, Control and Intelligent Systems
    JF  - Automation, Control and Intelligent Systems
    JO  - Automation, Control and Intelligent Systems
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    PB  - Science Publishing Group
    SN  - 2328-5591
    UR  - https://doi.org/10.11648/j.acis.20190701.16
    AB  - Motor-vehicle accidents have caused many safety concerns ever since cars have been on the road. With the implementation of cooperative and automated vehicles (CAVs) merging into the current crosswalks, signals, and concrete rules, the vehicle-pedestrian interactions create noteworthy safety issues. Through observational findings, intersections with higher signage and pedestrian signals had less likely of a chance for pedestrians to run into an altercation when compared to intersections with just crosswalks and no pedestrian signals. This research presents an optimization framework and an analytical solution with field observations to study whether the implementation of more pedestrian signals could have a great effect on vehicle/pedestrian incidents. The research implements the integrated methods of case studies, modeling and simulation using mathematical and statistical software on correlations and probabilities. This study adds minimal interference to the observations as they naturally occur. The study setting is non-contrived and maintained as natural environment. The collected data is continuous time series and measured using Chi-Square for analysis. After the identification of possible interactions between CAVs and pedestrians based on the data surveyed around the Illinois State University (ISU), this study finds that the safety of pedestrian relies on the intersection design of signs and signals more than the intelligence of CAVs (significance level = 95%). This paper also discusses law enforcement and autonomous driving as a means of lowering pedestrian incidents at intersections. The developed mathematical analysis model and simulations help to verify the influences of transportation signs and intersection designs. The investigation innovatively demonstrates the feasibilities of different methods to protect the pedestrian safety while they enter intersections. The findings from this research can provide decision support for future transportation design and implementation rules of CAVs.
    VL  - 7
    IS  - 1
    ER  - 

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Author Information
  • Department of Technology, Illinois State University, Normal IL, USA

  • Department of Technology, Illinois State University, Normal IL, USA

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